Issuu

XII

https://doi.org/10.22214/ijraset.2020.32549

December 2020

Study on Waste Water from Textile Industry Harjaspreet Singh1, Manpreet Kaur Verma2 1

Research Scholar, Desh Bhagat University, Mandi Gobindgarh, Fatehgarh Sahib. Assistant Professor, Department of Chemistry, Desh Bhagat University, Mandi Gobindgarh, Fatehgarh Sahib.

Abstract: Water pollution poses serious threats to both the environment and the organisms that depend on their environment for survival. Due to the toxicity from dyes in textile wastewater, there is a dire need for the development of innovative and efficient treatment technologies. In this study treatability studies, using a electrochemical treatment (ECT) method followed by activated carbon (AC) based adsorption. ECT method was studied extensively for the treatment of reactive black dye. Moreover, to understand the practical applicability of ECTs, the findings were optimized for treatment of synthetic textile wastewater (STW). Keywords: Textile, Industry, Waste Water, Treatment, Optimization I. INTRODUCTION Industrial development has introduced a large amount of waste materials into the water bodies. This activity has been going on since a long and continuous discharge of wastewater of industries has drastically affected the ecosystem. In the race of development, countries are lenient in setting the permissible limits and permitted discharge limits of the wastewater. Among the various industries, textile industries have been growing at a higher rate and the discharge of dyes from these industries highly alters the chemical composition of the water and water becomes unsuitable for drinking purposes. Therefore, removal of toxicants from the wastewaters of the textile industries has become a crucial issue in various nations. Among the various types of industries, dye and textile industries have a huge impact on human health. These industries comparatively generate a larger amount of wastewater. Dyeing and finishing operations in this industry uses a large amount of organic compounds which are not easily degraded and are dumped into the water bodies. Among the numerous organic dyes, azo dyes and its pigments are most used as they are easily bound to synthetic as well as natural textile fibers. For an instance, the major problem with these azo dyes is their complex chemical structure due to which they are not easily degraded by microorganisms and they get accumulated in different food chains (Pagga and Brown, 1986). Therefore, they finally enter into bodies of living beings and affect their body. These complex compounds if enter in human body could cause carcinogenic effects. Moreover, there are several other organic dyes such as: benzidine and other aromatic compounds, which have been reported to cause carcinogenic effects (Calrke and Anliker, 1980). In intestine of living beings these complex compounds are degraded into their monomers i.e. amines, which could cause serious health issues. Therefore, it is required to develop some new innovative technologies so as to the treat the wastewater containing dyes. Since last few decades, legislations have been made stricter for the pollution control and investments have been made, in research and development, to design some novel techniques for the treatment of effluent of textile industries. However, further research is still required to provide efficient solution for the emanating issues of treatment of effluent originating from textile industries. II. OBJECTIVES Broad objective of the study is to treat the effluent generated from a textile industry using a lab setup of electrochemical treatment. The other specific objectives that will be covered in this study are as follows: A. To estimate the impacts of operational parameters such as, initial pH, density and electrolysis time on the response parameters. The response parameters chosen for this study are, COD, Dye removal and energy consumption during the treatment process. B. In this way, central composite design of response surface methodology will be adopted to achieve maximum removal of COD and dye and simultaneously, the energy consumption of the treatment process will also be minimized. III. EXPERIMENTAL DESIGN AND PROCEDURE To develop a model emphasizing the relation between various factors was generated using a statistical approach. The operational parameters used for this analysis include, electric current passing through the electrodes, reaction time and initial pH of the reaction mixture. There impacts on the response parameters were estimated. The response parameters chosen in the present study were percentage removal of COD and dye and amount of energy consumption.

ÂŠIJRASET: All Rights are Reserved

661

International Journal for Research in Applied Science & Engineering Technology (IJRASET) ISSN: 2321-9653; IC Value: 45.98; SJ Impact Factor: 7.429 Volume 8 Issue XII Dec 2020- Available at www.ijraset.com The statistical approach adopted for this objective was a combination of a five-level central composite (CC) design and response surface methodology (RSM). Stat–Ease Design Expert (version 8.0.7.1) regression software was used for performing the statistical analysis. This approach is comparatively better than a time consuming and labor demanding one variable at a time (OVAT) approach. Also, this approach was used to design experiments and generate models based on linear or quadratic relations between the operating and response parameters (Banerji and Chaudhari, 2016). The relation developed between the operating and response parameters using this approach can be described using Eq. (3.1). = + + + + + + + + + (3.1) Where, X1-3 depicts the operating parameters which were chosen as X1 = electric current passing through the electrodes, mA/cm2; X2 = reaction time, min and X3 = initial pH of the reaction mixture. Y presents the response parameters, which were designated as Y1 = percentage removal of COD, %; Y2 = percentage removal of dye, % and Y3 = amount of energy consumption, KWh per litre of effluent treated; ci = response function coefficients which were determined using Stat–Ease Design Expert (version 8.0.7.1) regression software. Design Expert was further used to assess the adequacy of the generated models using analysis of variance (ANOVA). The various parameters calculated for the adequacy check were correlation regression coefficients, adjusted regression coefficients and goodness of fit. After all the statistical analysis, 3D plots of the results were also generated using RSM.

S.No.

Coded representation of operating parameters for statistical analysis Operating parameters Units Coded values -2

-1

mA/cm2

14.17

17.72

21.26

24.8

28.34

Current (X1)

Reaction time (X2)

min

67.5

105

142.5

180

Initial pH (X3)

5.5

8.5

IV. STATISTICAL ANALYSIS The quadratic equations presenting the relationship between the various input parameters, reduced snow albedo and enhanced snow melt were developed using BBD. The relationship between the input parameters and response parameters are described in Eq. (4.1) through Eq. (4.3). = 47.45 + 7.72 − 3.18 X − 4.91X + 5.71X − 5.56 (4.1) Where, Y1, X1, X2 and X3, depicts the % removal of COD electric current passing through the electrodes, reaction time and initial pH of the reaction mixture, respectively. The quadratic equation, developed using CCD for % removal of dye, is mentioned in Eq. (4.2). = 88.16 − 2.91 − 7.84 − 3.10 − 3.84 (4.2) Where, Y2 is percentage removal of dye. The quadratic equation, developed using CCD for amount of energy consumption, is mentioned in Eq. (4.3). = 0.00894 + 0.003171 + 0.002659 (4.3) Where, Y3 is the amount of energy consumed during the treatment process and all the response function coefficients in these equations are mentioned without considering their statistical significance. In order to validate the results generated from these models/equations, the values of response parameters, predicted using these models/equations, are compared with the experimental results, as shown in Table 4.1. Four different types of models were run to check the suitability for the experimental data. The four types of models identified were, linear, interactive, quadratic and cubic models. Among these four models, the most appropriate model was checked using sequential model sum of squares and model summary statistics. The results of this analysis are presented in Table 4.2, Table 4.3 and Table 4.4 for responses Y1, Y2 and Y3, respectively.

662

International Journal for Research in Applied Science & Engineering Technology (IJRASET) ISSN: 2321-9653; IC Value: 45.98; SJ Impact Factor: 7.429 Volume 8 Issue XII Dec 2020- Available at www.ijraset.com V. CONCLUSION The findings of this study made it evident that electrochemical process may prove to be an prominent technology for the treatment of synthetic textile wastewater. Based on the findings of this study several conclusions were drawn, which are discussed as following: A. RSM-based optimization of the treatment process proved that at optimum conditions of the response parameters, the values of operating parameters i.e., pH, current density and time were 6.25, 14.17 mA/cm2 and 102 min, respectively. B. At optimum conditions of the operating parameters, the values of response parameters i.e., % COD removal, % dye removal and consumption of energy during the treatment process, were observed to be 63.41%, 90.93% and 0.0035 KWh/per litre of th e STW treated, respectively. C. As value of pH was observed to be 6.25 at the optimum conditions, therefore, the species of aluminum hydroxide that were supposed to cause coagulation and adsorption would be Al(OH)3, Al(OH)2+ and Al(OH)2+. D. Kinetic studies showed that EC based treatment of STW followed first order kinetics and the kinetic constants at 30°C for each response parameter i.e., % COD removal and % dye removal were 0.0205 min-1 and 0.0097 min-1, respectively. Similarly, at 50°C the kinetic constants for % COD removal and % dye removal were 0.037 min-1 and 0.011 min-1, respectively. E. Amount of Al in the treated STW, sludge and scum was observed to be 25.16 mg/l, 0.50778g and 0.06006 g, respectively. REFERENCES [1] [2] [3] [4] [5]

[6] [7] [8] [9] [10] [11] [12] [13] [14] [15]

A.R. Khataee, V. Vatanpour, A.R.A. Ghadim, “Decolorization of acid blue 9 solution by UV/Nano-TiO2, Fenton, Fenton-like,electro-Fenton and electrocoagulation processes” , Journal of Hazardous Materials, 161 (2009) 1225–1233. B.K. Korbahti, A. Tanyolac, “Electrochemical treatment of simulated textile wastewater with industrial components and Levafix Blue CA reactive dye: Optimization through response surface methodology”, Journal of Hazardous Materials, 151 (2008) 422–431. A. Georgiou, P. Melidis, A. Aivasidis, “Use of a microbial sensor: inhibition effect of azo-reactive dyes on activated sludge”, Bioprocess and Biosystem Engineering, 25 (2002) 79-83. D. Ghosh, C.R. Medhi, H. Solanki, M.K. Purkait, “Decolorization of Crystal Violet Solution by Electrocoagulation”, Journal of Environmental Protection Science, 2 (2008) 25 – 35. H. Zhian, K. khalipour, H. khandani, “The removal Acid Red Dye 88(AR88) from aqueous solution by electrocoagulation”, World applied Sciences Journal, 3 (2011) 558-563. H.R. Guendy, “Treatment and Reuse of Wastewater in the Textile Industry by Means of Coagulation and Adsorption Techniques” Journal of Applied Sciences Research, 6(8) (2010) 964-972. H.M.F. Freundlich, “Over the adsorption in solution”, Journal of Physical Chemistry, 57 (1906) 385-471. I.A. Sengil, M. Ozacar, “The decolorization of C.I. reactive black 5 in aqueous solution by electrocoagulation using sacrificial iron electrodes”, Journal of Hazardous Materials, 161 (2009) 1369–1376. I. Langmuir, “The adsorption of gases on plane surfaces of glass, mica and platinum”, Journal of American Chemical Society 40 (1918) 1361-1403. B. Merzouk, K. Madani, A. Sekki, “Using electro coagulation electro flotation technology to treat synthetic solution and textile wastewater”, Desalination, 250 (2010) 573–577. Phalakornkule, S. Polgumhang, W. Tongdaung, B. Karakat, T. Nuyut, “Electrocoagulation of blue reactive, red disperse and mixed dyes and applicationin treating textile effluent”, Journal of Environmental Management, 91 (2010) 918– 926. Sharma, A., Singh, S., Experimental study on use of waste hdpe, ldpe and chloroprene rubber in bituminous concrete, International Journal of Innovative Technology and Exploring Engineering, 2019, 8(8), pp. 306-311 Sidhu, B.S., Sharda, R., Singh, S., Spatio-Temporal assessment of groundwater depletion in Punjab, India, Groundwater for Sustainable Development, 2020, 100498. Thakur, A., Singh, S., Experimental investigation on higher proportion of recycled asphalt pavement mixture for road construction, International Journal of Innovative Technology and Exploring Engineering, 2019, 8(8), pp. 3311-3315 J. Duan, J. Gregory, “Coagulation by hrdrolysing metal salts”, Advanced Journal of Colloid and Interface Science, 100–102 (2003) 475–502. J. Liang, L. Cui, X. Wang, J.L. Liu, H. Wang, Y. Liu,” Study on the Treatment of Dye Wastewater by Electro-coagulation”, Department of chemistry and environment, School of Science, Shenyang University of Technology, 110023 Shenyang, China.

663